Analytics Engineer: Build Scalable Data Pipelines & Insights

Lyka; City of Melbourne; On-site; AUD 110,000 - 140,000; Full time

Benefits offered by this job

Up to 18 weeks of paid parental leave

Wellbeing assistance and tools

Dog-friendly offices and support for/p

Pupper parent support and pet-friendly

Job summary

Lyka, an Australian pet wellness company, is hiring a Data Analytics Engineer to enable data-driven decisions across the business. You'll partner with Analysts and collaborate with Product and Engineering to build scalable data products and provide self-service data access through a semantic layer.

You will bridge data engineering and analytics, delivering fast, trustworthy insights via well-modeled data, intuitive tools, and robust pipelines.

Qualifications

• 1+ years experience in data modelling, analytics engineering, or BI development.
• Strong proficiency in SQL and experience with dbt, Airflow, and modern data warehouses.
• Familiarity with BI tools (Looker, Tableau, Omni) and designing scalable dashboards.
• Solid understanding of data lifecycle and analytics workflows from ingestion to insight.
• Experience collaborating with Analytics, Product and Engineering teams to deliver data solutions.
• Basic understanding of using AI tools to optimise day-to-day processes.

Responsibilities

• Design and implement analytics-ready data models to enable data capabilities and decision-making.
• Build and maintain robust, scalable data pipelines using dbt, Airflow, and Python.
• Develop semantic layers and metrics definitions to support consistent reporting.
• Ensure data quality, reliability, and performance across analytics workflows.

Skills

Analytics engineering

Data modelling

BI development

SQL

Cross-functional collaboration

Data quality

Tools

dbt

Airflow

Snowflake

BigQuery

Looker

Tableau

Omni

Job description

Lyka, an Australian pet wellness company, is hiring a Data Analytics Engineer to enable data-driven decisions across the business. You'll partner with Analysts and collaborate with Product and Engineering to build scalable data products and provide self-service data access through a semantic layer.

You will bridge data engineering and analytics, delivering fast, trustworthy insights via well-modeled data, intuitive tools, and robust pipelines.